Temporal orientation refers to an individual’s
tendency to connect to the psychological concepts of past, present or future, and it affects personality, motivation, emotion, decision making and stress coping processes.
The study of the social media users’ psychodemographic attributes from the perspective of
human temporal orientation can be of utmost
interest and importance to the business and
administrative decision makers as it can provide an extra precious information for them to
make informed decisions. In this paper, we
propose a very first study to demonstrate the
association between the sentiment view of the
temporal orientation of the users and their different psycho-demographic attributes by analyzing their tweets. We first create a temporal orientation classifier in a minimally supervised way which classifies each tweet of
the users in one of the three temporal categories, namely past, present, and future. A
deep Bi-directional Long Short Term Memory
(BLSTM) is used for the tweet classification
task. Our tweet classifier achieves an accuracy
of 78.27% when tested on a manually created
test set. We then determine the users’ overall
temporal orientation based on their tweets on
the social media. The sentiment is added to
the tweets at the fine-grained level where each
temporal tweet is given a sentiment with either
of the positive, negative or neutral. Our experiment reveals that depending upon the sentiment view of temporal orientation, a user’s attributes vary. We finally measure the correlation between the users’ sentiment view of temporal orientation and their different psychodemographic factors using regression.